meta: Muse Spark 1.1
meta/muse-spark-1.1
Access Muse Spark 1.1 from meta using Puter.js AI API.
Get Started// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "meta/muse-spark-1.1"
}).then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms", {
model: "meta/muse-spark-1.1"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
# pip install openai
from openai import OpenAI
client = OpenAI(
base_url="https://api.puter.com/puterai/openai/v1/",
api_key="YOUR_PUTER_AUTH_TOKEN",
)
response = client.chat.completions.create(
model="meta/muse-spark-1.1",
messages=[
{"role": "user", "content": "Explain quantum computing in simple terms"}
],
)
print(response.choices[0].message.content)
curl https://api.puter.com/puterai/openai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
-d '{
"model": "meta/muse-spark-1.1",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Muse Spark 1.1 is a multimodal reasoning model from Meta Superintelligence Labs, built for agentic workflows. It accepts text, images, video, audio, and PDF documents as input and returns text, with a 1,048,576-token context window.
The model is designed to orchestrate multi-agent workflows, acting as either a main agent that plans and delegates tasks or as a subagent, and it generalizes zero-shot to new tools, MCP servers, and custom skills. It supports parallel function calling, structured output, built-in search with citations, and configurable reasoning effort, and Meta reports strong results on coding across large codebases, computer-use tasks, and visual-to-code generation.
This is Meta's first model available through a paid API, priced at $1.25 per million input tokens and $4.25 per million output tokens, aimed at developers building agentic coding tools and enterprise workflow automation.
Context Window 1M
tokens
Max Output N/A
tokens
Input Cost $1.25
per million tokens
Output Cost $4.25
per million tokens
Input text, image, video, audio, pdf
modalities
Tool Use Yes
Release Date Jul 16, 2026
Output Speed 121
tokens / sec
Latency 0.84s
time to first token
Model Playground
Try Muse Spark 1.1 instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How Muse Spark 1.1 performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 89.8% |
| Humanity's Last Exam Cross-domain reasoning | 45.1% |
| SciCode Scientific programming | 58.2% |
| LCR Long-context reasoning | 63.3% |
Scores sourced from Artificial Analysis.
Frequently Asked Questions
You can access Muse Spark 1.1 by meta through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Muse Spark 1.1 to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $1.25 |
| Output | $4.25 |
Muse Spark 1.1 was created by meta and released on Jul 16, 2026.
Muse Spark 1.1 supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,097 pages of text.
Muse Spark 1.1 accepts the following input types: text, image, video, audio, pdf. It produces: text.
Yes, Muse Spark 1.1 supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Muse Spark 1.1 scores 50.6 on the Artificial Analysis Intelligence Index, outperforming 96% of tracked models. On coding, it scores 71.3 (outperforms 91% of models).
Yes — the Muse Spark 1.1 API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Get started with Puter.js
Add Muse Spark 1.1 to your app without worrying about API keys or setup.
Read the Docs View Tutorials